Allocation of temporary disaster response facilities under demand uncertainty: An earthquake case study

ÇAVDUR F., KÖSE KÜÇÜK M., Sebatli A.

INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, cilt.19, ss.159-166, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1016/j.ijdrr.2016.08.009
  • Dergi Adı: INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.159-166
  • Anahtar Kelimeler: Disaster operations management, Disaster relief operations, Facility allocation, Relief supplies distribution, Temporary disaster response facility, Stochastic programming, EMERGENCY RESPONSE, OR/MS RESEARCH, EVACUATION, MODEL, OPTIMIZATION, FORMULATION, LOCATION
  • Bursa Uludağ Üniversitesi Adresli: Evet

Özet

In this paper, we consider the problem of temporary disaster response facility allocation for temporary or short-term disaster relief operations, propose a solution approach and illustrate it with an earthquake case study in Turkey. A two-stage stochastic program is developed for the solution of the problem to minimize the total distance traveled, the unmet demand and the total number of facilities (considering the potential difficulties to access the facilities), where facility allocation and service decisions are performed in the first and second stages, respectively. An earthquake case study developed by the Prime Ministry Disaster and Emergency Management Authority (mostly referred as AFAD in Turkey) is used to test our model. We use five different scenarios, each representing a different after-disaster situation (i.e., traffic conditions, time etc.), with its respective probability of occurrence, to model the demand uncertainty for relief supplies. We first solve the deterministic model for each scenario, and then, the corresponding stochastic program. In addition to the defined objectives of the model, quality of each solution is analyzed in terms of average walking distance, demand satisfaction rate and average facility utilization. (C) 2016 Elsevier Ltd. All rights reserved.